Accessing ampli-tonotopic organization of rat auditory cortex by microstimulation of cochlear nucleus

Auditory brainstem implants (ABI) that electrically stimulate the surface of cochlear nucleus have been clinically used for the rehabilitation of deaf patients with bilateral vestibular schwannomas. The change of pitch perception with an active electrode location is not as clear in ABIs as in cochlear implants, a factor which might play a role in poorer speech performance in ABIs. The objective of present work was to develop an animal ABI model that could provide physiological data for future ABI development and optimization. The experimental system included a penetrating microelectrode array for microstimulation of the cochlear nucleus and a surface microelectrode array for mapping evoked potentials over the auditory cortex. We first obtained tone-evoked cortical activation patterns, which represented a place code of the frequency and intensity of test tones, i.e., the ampli-tonotopic organization, and compared the patterns with those evoked by cochlear nuclear microstimulation. Our experimental results demonstrated that microstimulation of both the dorsal and ventral cochlear nucleus (DCN and VCN) could access the cortical ampli-tonotopic organization as acoustic stimuli did. We also found that the cortical dynamic range was wider for the DCN than VCN stimulation and for the low-frequency than for the high-frequency pathway. The present results have great implications for improved ABI performance.     

Automatic contour definition on left ventriculograms by image evidence and a multiple template-based model

An algorithm which utilizes digital image processing and pattern recognition methods for automated definition of left ventricular (LV) contours is presented. Digital image processing and pattern recognition techniques are applied to digitally acquired radiographic images of the heart to extract the LV contours required for quantitative analysis of cardiac function. Knowledge of the image domain is invoked at each step of the algorithm to orient the data search and thereby the complexity of the solution. A knowledge-based image transformation, directional gradient search, expectations of object versus background location, least-cost path searches by dynamic programming, and a digital representation of possible versus impossible ventricular shape are exploited. The digital representation, composed of a set of characteristic templates, was created using contours obtained by manual tracing. The algorithm was tested by application of three sets of 25 images each. Test set one and two were used as training sets for creation of the model for contour correction. Model-based correction proved to be an effective technique, producing significant reduction of error in the final contours.     

Centralized dynamic frequency allocation for cell-edge demand satisfaction in fractional frequency reuse networks

Fractional frequency reuse (FFR) has emerged as a well-suited remedy for inter-cell interference reduction in the next-generation networks by allocating frequency reuse factor (FRF) of unity for the cell-center (CC) and higher FRF for the cell-edge (CE) users. However, this strict FFR comes at a cost of equal partitioning of frequency resources to the CE which most likely has varying demands in current networks. In order to mitigate this, we propose a centralized dynamic resource allocation scheme which allocates demand-dependent resources to CE users. The proposed scheme therefore outperforms the fixed allocation scheme of strict FFR for both CC and CE users. Complexity analysis provides a fair means of analyzing the suitability of proposed algorithm. We have also compared the proposed methodology with a reference dynamic fractional frequency reuse (DFFR) scheme. Results show maximum performance gain of up to 30% for 3 reference cells employing Rayleigh fading—through normalized area spectral efficiency (ASE) analysis for both fixed allocation and DFFR. Spectral efficiency analysis also indicates per-cell performance gain for both CC and CE users. Further, detailed three-dimensional ASE plots give insights into the affects to other cells. Due to dynamic nature of traffic loads, the proposed scheme is a candidate solution for satisfying the demands of individual cells.     

Dynamic fractional frequency reuse (D‐FFR) for multicell OFDMA networks using a graph framework

A graph‐based framework is proposed in this paper to implement dynamic fractional frequency reuse (D‐FFR) in a multicell Orthogonal Frequency Division Multiple Access (OFDMA) network. FFR is a promising resource‐allocation technique that can effectively mitigate intercell interference (ICI) in OFDMA networks. The proposed D‐FFR scheme enhances the conventional FFR by enabling adaptive spectral sharing as per cell‐load conditions. Such adaptation has significant benefits in practical systems where traffic loads in different cells are usually unequal and time‐varying. The dynamic adaptation is accomplished via a graph framework in which the resource‐allocation problem is solved in two phases: (1) constructing an interference graph that matches the specific realization of FFR and the network topology and (2) coloring the graph by use of a heuristic algorithm. Various realizations of FFR can easily be incorporated in the framework by manipulating the first phase. The performance improvement enabled by the proposed D‐FFR scheme is demonstrated by computer simulation for a 19‐cell network with equal and unequal cell loads. In the unequal‐load scenario, the proposed D‐FFR scheme offers significant performance improvement in terms of cell throughput and service rate as compared to conventional FFR and previous interference management schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

A novel speech-processing strategy incorporating tonal information for cochlear implants

Good performance in cochlear implant users depends in large part on the ability of a speech processor to effectively decompose speech signals into multiple channels of narrow-band electrical pulses for stimulation of the auditory nerve. Speech processors that extract only envelopes of the narrow-band signals (e.g., the continuous interleaved sampling (CIS) processor) may not provide sufficient information to encode the tonal cues in languages such as Chinese. To improve the performance in cochlear implant users who speak tonal language, we proposed and developed a novel speech-processing strategy, which extracted both the envelopes of the narrow-band signals and the fundamental frequency (F0) of the speech signal, and used them to modulate both the amplitude and the frequency of the electrical pulses delivered to stimulation electrodes. We developed an algorithm to extract the fundatmental frequency and identified the general patterns of pitch variations of four typical tones in Chinese speech. The effectiveness of the extraction algorithm was verified with an artificial neural network that recognized the tonal patterns from the extracted F0 information. We then compared the novel strategy with the envelope-extraction CIS strategy in human subjects with normal hearing. The novel strategy produced significant improvement in perception of Chinese tones, phrases, and sentences. This novel processor with dynamic modulation of both frequency and amplitude is encouraging for the design of a cochlear implant device for sensorineurally deaf patients who speak tonal languages.     

Encoding frequency modulation to improve cochlear implant performance in noise

Different from traditional Fourier analysis, a signal can be decomposed into amplitude and frequency modulation components. The speech processing strategy in most modern cochlear implants only extracts and encodes amplitude modulation in a limited number of frequency bands. While amplitude modulation encoding has allowed cochlear implant users to achieve good speech recognition in quiet, their performance in noise is severely compromised. Here, we propose a novel speech processing strategy that encodes both amplitude and frequency modulations in order to improve cochlear implant performance in noise. By removing the center frequency from the subband signals and additionally limiting the frequency modulation's range and rate, the present strategy transforms the fast-varying temporal fine structure into a slowly varying frequency modulation signal. As a first step, we evaluated the potential contribution of additional frequency modulation to speech recognition in noise via acoustic simulations of the cochlear implant. We found that while amplitude modulation from a limited number of spectral bands is sufficient to support speech recognition in quiet, frequency modulation is needed to support speech recognition in noise. In particular, improvement by as much as 71 percentage points was observed for sentence recognition in the presence of a competing voice. The present result strongly suggests that frequency modulation be extracted and encoded to improve cochlear implant performance in realistic listening situations. We have proposed several implementation methods to stimulate further investigation. Index Terms-Amplitude modulation, cochlear implant, fine structure, frequency modulation, signal processing, speech recognition, temporal envelope.     

Robust contour tracking based on a coupling between geodesic active contours and conditional random fields

This paper presents a new general framework for contour tracking based on the synergy of two powerful segmentation tools, namely, spatial temporal conditional random fields (CRFs) and geodesic active contours (GACs). The contours of targets are modeled using a level set representation. The evolution of the level sets toward the target contours is formulated as one of the joint region-based (CRF) and boundary-based (GAC) segmentations under a unified Bayesian framework. A variational inference technique is used to solve this otherwise intractable inference problem, leading to approximate MAP solutions of both the new 3D spatial temporal CRF and the GAC model. The tracking result of the previous frame is used to initialize the curve in the current frame. Typical contour tracking problems are considered and experimental results are given to illustrate the robustness of the method against noise and its accurate performance in moving objects boundary localization.     

A Novel Hierarchical Two-Level Spectral Preconditioning Technique for Electromagnetic Wave Scattering

A new set of higher order hierarchical basis functions based on curvilinear triangular patch is proposed for expansion of the current in electrical field integral equations solved by method of moments. The hierarchical two-level spectral preconditioning technique is developed for the generalized minimal residual iterative method, in which the multilevel fast multipole method is used to accelerate matrix-vector product. The sparse approximate inverse (SAI) preconditioner based on the higher order hierarchical basis functions is used to damp the high frequencies of the error and the low frequencies is eliminated by a spectral preconditioner in a two-level manner defined on the lower order basis functions. The spectral preconditioner is combined with SAI preconditioner to obtain a hierarchical two-level spectral preconditioner. Numerical experiments indicate that the new preconditioner can significantly reduce both the iteration number and computational time.     

Iterative key frame selection in the rate-constraint environment

Video representation through key frames has been addressed frequently as an efficient way of preserving the whole temporal information of sequence with a considerably smaller amount of data. Such compact video representation is suitable for the purpose of video browsing in limited storage or transmission bandwidth environments. In this case, the controllability of the total key frame number (i.e. key frame rate) depending on the storage or bandwidth capacity is an important requirement for the key frame selection method. In this paper, we present a sequential key frame selection method when the number of key frames is given as a constraint. It first selects the pre-determined number of initial key frames and time-intervals. Then, it adjusts the positions of key frames and time-intervals by iteration, which reduces the distortion step by step. Experimental results demonstrate the improved performance of our algorithm over the existing approaches.     

Downlink Transmit Power Allocation in Soft Fractional Frequency Reuse Systems

Downlink transmit power allocation schemes are proposed for soft fractional frequency reuse (FFR) in loose and tightly coordinated systems. The transmit powers are allocated so that the loss of spectral efficiency from the soft FFR is minimized, and the required cell edge user throughput is guaranteed. The effect of the soft FFR on spectral efficiency is evaluated depending on the power allocation schemes and the number of subbands. Results show that the loss of spectral efficiency from the soft FFR can be reduced by configuring an appropriate number of subbands in the loosely coordinated systems. In tightly coordinated systems, results show that the loss of spectral efficiency can be minimized regardless of the number of subbands due to its fast coordination.     

Iterative analysis of finite-sized planar frequency selective surfaces with rectangular patches or perforations

Frequency selective surfaces (FSS) and other periodic gratings are often analyzed under the assumption that they are infinite in extent. Most existing methods for analyzing periodic structures are based on the use of a Floquet-type representation of the fields in a unit cell whose dimensions are typically comparable to the wavelength. In this work, a finite, truncated, version of an infinite periodic structure is dealt with directly, without the benefit of the assumption that the structure is periodic. This, in turn, requires the handling of a large number of unknowns and makes it difficult to solve the problem using conventional matrix methods. Two different iteration approaches to solving the finite FSS problem are discussed in the paper both of which employ the spectral domain formulation. The first of these employs the spectral iteration technique and the second one uses the conjugate gradient (CG) iteration algorithm. Convergence characteristics of both of these methods are investigated and the results are reported.     

Interference management with adaptive fractional frequency reuse for LTE-A femtocells networks

This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse (FFR) scheme for macro and femto networks. The strategy aims to maximize the system throughput taking into account a number of system constraints. Here, the system constrains consist of the outage constraints of two-tier users and macrocell spectral efficiency requirement. The detailed procedures of our proposed strategy are: 1) A reference signal received power (RSRP) based selection algorithm is presented to adaptively select the optional FFR schemes satisfying the outage constraints. 2) Considering the macrocell spectral efficiency, the optimal FFR scheme is selected from the optional FFR schemes at MeNB side, to achieve the maximum system throughput in two-tier femtocell networks. We study the efficacy of the proposed strategy using an long term evolution advanced (LTE-A) system level simulator. Simulation results show that our proposed interference management strategy can select the best FFR scheme to maximize the system throughput, and the FFR schemes derived by using RSRP-based selection algorithm can be the effective solutions to deploy femtocells in macrocells.     

A faster converging snake algorithm to locate object boundaries.

A different contour search algorithm is presented in this paper that provides a faster convergence to the object contours than both the greedy snake algorithm (GSA) and the fast greedy snake (FGSA) algorithm. This new algorithm performs the search in an alternate skipping way between the even and odd nodes (snaxels) of a snake with different step sizes such that the snake moves to a likely local minimum in a twisting way. The alternative step sizes are adjusted so that the snake is less likely to be trapped at a pseudo-local minimum. The iteration process is based on a coarse-to-fine approach to improve the convergence. The proposed algorithm is compared with the FGSA algorithm that employs two alternating search patterns without altering the search step size. The algorithm is also applied in conjunction with the subband decomposition to extract face profiles in a hierarchical way.     

Performance analysis of hexagonal cellular networks in fading channels

This paper analyzes the location‐dependent performance metrics of coverage probability and spectral efficiency in hexagonal cellular networks under Rayleigh fading with a general distribution for shadowing and also including two special cases of no shadowing and lognormal shadowing. The effects of system parameters such as frequency reuse factor, transmission probability of base stations, and signal‐to‐interference‐plus‐noise ratio gap from Shannon capacity are accurately characterized. The proposed approach is applied to fractional frequency reuse (FFR) scheme where the impact of FFR on spectral efficiency is evaluated. Numerical results show that (i) in a lognormal‐shadowed Rayleigh fading channel with the shadowing standard deviation of 12 dB, the cell area wide spectral efficiency is degraded by approximately 40% compared with when there is Rayleigh fading without shadowing; (ii) the improvement in spectral efficiency achieved by FFR over the universal frequency reuse increases as the transmission probability increases and the shadowing becomes less severe; and (iii) in Rayleigh fading without shadowing environment where all the base stations are actively transmitting, FFR achieves approximately 20% improvement in spectral efficiency in the cell edge area. Interestingly, this improvement increases to about 30% if a 3‐dB signal‐to‐interference‐plus‐noise ratio gap from Shannon capacity is further accounted. Copyright © 2015 JohnWiley & Sons     

基于脊波和神经网络的大压缩比遥感图像压缩

为了实现大压缩比的遥感图像压缩,利用神经网络的自组织、并行计算和分布式存储的能力,提出一种基于神经网络的压缩方法.在传统单隐层前向神经网络的基础上,该网络使用一种新的能有效处理直线型和曲线型奇异性的多尺度几何分析工具-脊波,作为隐层神经元的激活函数.它不仅具有神经网络压缩的优点;并且由于脊波良好的时、频和方向局域化特性,能够对遥感图像的边缘和轮廓实现更加有效的表示.仿真结果表明:该方法不仅能实现较高的压缩比,而且具有重建图像质量好、学习快速和鲁棒性强等优点.     

Robust hybrid pitch detector

A hybrid pitch detector characterised by parallel analysis of the speech signal in temporal, spectral and cepstral domains is proposed. The voiced/unvoiced decision and pitch period evaluation is realised by a logical analysis of the results from three domains. The experimental analysis shows the robustness of the detector for noisy and telephone speech.<>     

Expediting the identification of impaired channels in cochlear implants via analysis of speech-based confusion matrices

There is significant variability in the benefit provided by cochlear implants to severely deafened individuals. The reasons why some subjects exhibit low speech recognition scores are unknown; however, underlying physiological or psychophysical factors may be involved. Certain phenomena, such as indiscriminable electrodes and nonmonotonic pitch rankings, might hint at limitations in the ability of individual channels in the cochlear implant and/or sensorineural pathway to convey speech information. In this paper, four approaches for analyzing the results of a simple listening test using speech stimuli are investigated for the purpose of targeting channels of concern in order for follow-on psychophysical experiments to correctly identify channels performing in an "impaired" or anomalous manner. Listening tests were first conducted with normal-hearing subjects and acoustic models simulating channel-specific anomalies. Results indicate that these proposed analyses perform significantly better than chance in providing information about the location of anomalous channels. Vowel and consonant confusion matrices from six cochlear implant subjects were also analyzed to test the robustness of the proposed analyses to variability intrinsic to cochlear implant data. The current study suggests that confusion matrix analyses have the potential to expedite the identification of impaired channels by providing preliminary information prior to exhaustive psychophysical testing.     

Hyperspectral image data analysis

The fundamental basis for space-based remote sensing is that information is potentially available from the electromagnetic energy field arising from the Earth's surface and, in particular, from the spatial, spectral, and temporal variations in that field. Rather than focusing on the spatial variations, which imagery perhaps best conveys, why not move on to look at how the spectral variations might be used. The idea was to enlarge the size of a pixel until it includes an area that is characteristic from a spectral response standpoint for the surface cover to be discriminated. The article includes an example of an image space representation, using three bands to simulate a color IR photograph of an airborne hyperspectral data set over the Washington, DC, mall     

Performance evaluation of an adaptive self-organizing frequency reuse approach for OFDMA downlink

Orthogonal frequency division multiple access (OFDMA) is extensively utilized for the downlink of cellular systems such as long term evolution (LTE) and LTE advanced. In OFDMA cellular networks, orthogonal resource blocks can be used within each cell. However, the available resources are rare and so those resources have to be reused by adjacent cells in order to achieve high spectral efficiency. This leads to inter-cell interference (ICI). Thus, ICI coordination among neighboring cells is very important for the performance improvement of cellular systems. Fractional frequency reuse (FFR) has been widely adopted as an effective solution that improves the throughput performance of cell edge users. However, FFR does not account for the varying nature of the channel. Moreover, it exaggerates in caring about the cell edge users at the price of cell inner users. Therefore, effective frequency reuse approaches that consider the weak points of FFR should be considered. In this paper, we present an adaptive self-organizing frequency reuse approach that is based on dividing every cell into two regions, namely, cell-inner and cell-outer regions; and minimizing the total interference encountered by all users in every region. Unlike the traditional FFR schemes, the proposed approach adjusts itself to the varying nature of the wireless channel. Furthermore, we derive the optimal value of the inner radius at which the total throughput of the inner users of the home cell is as close as possible to the total throughput of its outer users. Simulation results show that the proposed adaptive approach has better total throughput of both home cell and all 19 cells than the counterparts of strict FFR, even when all cells are fully loaded, where other algorithms in the literature failed to outperform strict FFR. The improved throughput means that higher spectral efficiency can be achieved; i.e., the spectrum, which is the most precious resource in wireless communication, can be utilized efficiently. In addition, the proposed algorithm can provide significant power saving, that can reach 50% compared to strict FFR, while not penalizing the throughput performance.

     

Intra‐ and Inter‐frame Features for Automatic Speech Recognition

In this paper, alternative dynamic features for speech recognition are proposed. The goal of this work is to improve speech recognition accuracy by deriving the representation of distinctive dynamic characteristics from a speech spectrum. This work was inspired by two temporal dynamics of a speech signal. One is the highly non‐stationary nature of speech, and the other is the inter‐frame change of a speech spectrum. We adopt the use of a sub‐frame spectrum analyzer to capture very rapid spectral changes within a speech analysis frame. In addition, we attempt to measure spectral fluctuations of a more complex manner as opposed to traditional dynamic features such as delta or double‐delta. To evaluate the proposed features, speech recognition tests over smartphone environments were conducted. The experimental results show that the feature streams simply combined with the proposed features are effective for an improvement in the recognition accuracy of a hidden Markov model–based speech recognizer.